A Systematic Literature Review of AI-Based Chatbots' Impact on Operational Consistency in Customer Service

This study aims to review the AI based Chatbots' impact on operational consistency in customer service. The implementation of AI Chatbots in customer service represents a strategic innovation for enhancing operational consistency. This research conducts a systematic literature review of AI-Based Chatbot, emphasizing recent developments and key studies published between 2019 and 2025. Data were comprehensively collected from three major academic databases-IEEE, Springer, and ScienceDirect. Using the PRISMA framework, a total of 26 relevant studies were identified and included for analysis. This study analyzes the impact of chatbots by comparing them to traditional human-agent services, examining the influence of demographic factors, and identifying their effect on customer satisfaction alongside the commonly employed algorithms. The findings reveal that customer satisfaction is significantly driven by rapid response times, 24/7 availability, system and information quality, and personalization. From a technical perspective, the selection of algorithms-such as Transformer-Based Models for high accuracy or LSTM for cost-effective implementations-must be aligned with specific operational requirements. The primary future challenge lies in reconciling the standardized service delivery of chatbots with the personalized engagement that remains a distinctive strength of human agents.